NYU big data project to pinpoint undiagnosed diabetes patients

Philadelphia insurer Independence Blue Cross (IBC), New York University (NYU) and NYU Langone Medical Center are jointly collaborating to develop machine-learning algorithms to identify undiagnosed diabetes and pre-diabetes in patients, according to NYU’s April 29 announcement.

The project, funded by a three-year grant from IBC, will take place within NYU’s Initiative in Data Science and Statistics. The collaborators ultimately seek to harness IBC medical and pharmacy claims data to improve care and lower costs through early detection of the disease.

Of the 25 million people with diabetes in the United States, one-third is unaware they have the disease, according to the American Diabetes Association. Moreover, the association estimates that 79 million people have pre-diabetes. “The pre-diabetes stage is a critical one. If hyperglycemia goes untreated, damage to the blood vessels begins and the risk of cardiovascular disease increases,” according to the announcement.

“Without a doubt, improved ways to accelerate the diagnosis of diabetes in affected people will improve health, reduce the complications of the disease, and reduce health care costs,” said Ann Marie Schmidt, MD, a professor of endocrinology and medicine at NYU Langone Medical Center and co-investigator.

NYU Assistant Professor David Sontag, who works in the department of computer science at Courant Institute of Mathematical Sciences, will lead the effort.